Our products are developed for health monitoring, diagnostics, and predictive maintenance of rotating machines and are a part of the Enertics
Asset Health Monitoring and Management suite of applications.

eM PreA



 It features AI-based sensor data prediction analytics as well as a machine learning-based alert management system that alerts users about potentially harmful machine conditions.

The revolutionary eM PreA module automatically evaluates sensor data to discover anomalies before they become major problems.


– Predictive Checks are required for almost all electrical or mechanical systems to avoid unexpected failures
– Troubleshooting issues after the failures costs a lot of money for the equipment owners and operators
– Predominantly there is no proactive information available to detect machine irregularities before they turn into major issues
– Even though a large amount of sensor data is generated by a range of industrial assets, finding Trained Resources to spot defects in advance remains a challenge


– Need for an AI Automated Predictive Analytic Tool is required to deliver relevant insights to the maintenance personnel
– This technique should aid in the early detection of asset issues before they develop into a crisis
– A Well-Designed Predictive System assists users in Early Predictions and Diagnosis of Potential Issues with their critical equipment
– To focus on Processess that will help establish an Effective Asset Performance Management (APM) system to reduce Asset Downtime and Production Losses.


– Innovative and automatic evaluation of sensor data to detect anomalies before they turn into significant issues.
– Algorithms to predict individual fault conditions.
– With advanced sensors, not only it is possible to forecast individual sensor data, but it is also possible to predict specific machine faults
– Multi-Application based Solution

For more information regarding eM PreA, download the pdf below.

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